MSK Initiatives

The Halvorsen Center for Computational Oncology

The Halvorsen Center for Computational Oncology (CCO) integrates data science, artificial intelligence, and algorithm development to advance cancer research at Memorial Sloan Kettering (MSK). The center pushes scientific boundaries through computational analysis of extensive patient and experimental data. Supported by Diane and Andreas Halvorsen, the center promotes excellence in computing-based research, driving innovations like personalized medicine, cancer vaccines, and insights into tumor biology, with numerous breakthroughs published in high-impact journals.

cBioPortal

The cBioPortal for Cancer Genomics provides visualization, analysis, and download of large-scale cancer genomics data sets. A public instance of cBioPortal is hosted and maintained by Memorial Sloan Kettering Cancer Center. It provides access to data by The Cancer Genome Atlas as well as many carefully curated published data sets. The cBioPortal software can be used to for local instances that provide access to private data.

Comp IO

As cancer immunotherapies have emerged as front-line therapies, it has become clear that advancing computational approaches to cancer immunology is critical to better understanding the role of the immune system in cancer. Despite the enormous promise of immunotherapy, success is still limited to a minority of patients and tumor types. Through a better quantitative understanding of how immunotherapies work and how the immune system reacts to them, the Program in Computational Immuno-Oncology hopes to play a role in extending the benefit of immunotherapies to a larger set of patients, and in gaining new insights on malignant-immune cell interactions.

DLP

Direct Library Preparation (DLP) is a platform for scalable single cell whole genome sequencing originally developed at BC Cancer, soon to be available at MSK. DLP generates low pass whole genome sequence and matched images for up to ~5000 cells in one run and can be used to study mutational processes, tumor evolution, cell division and cell morphology. A multi-institutional effort centered at MSK aims to build computational methods and infrastructure to support the platform.

isabl

Isabl is a plug-and-play framework for scalable bioinformatics operations designed to support automated processing and management of NGS assets and their metadata. An active instance is available on the Memorial Sloan Kettering internal network here, and a public site is available at isabl.io.

MSK Kids Genome

​As part of the Pediatric Translational Medicine Program (PTMP), the Papaemmanuil lab has established a clinical prototype Whole Genome and Transcriptome Sequencing (WGTS) platform analytical workflow. Currently 1 in 2 pediatric cancers do not benefit from established molecular diagnostic tests. Leveraging automations from Isabl platform and information from our institutional knowledge base OncoKb, we process WGTS data to rapidly identify disease defining, prognostic and therapy informing biomarkers. This research initiative will guide the development of clinical diagnostic applications based on WGTS genomic applications in cancer care.

MSK-IMPACT

MSK-IMPACT™ stands for integrated mutation profiling of actionable cancer targets. It is a targeted tumor-sequencing test available to Memorial Sloan Kettering patients. MSK-IMPACT can detect mutations and other critical changes in the genes of both rare and common cancers. With the MSK-IMPACT test, doctors can quickly find out whether a tumor has changes that make the cancer vulnerable to particular drugs. MSK patients can then be matched to the available therapies or clinical trials that will most benefit them.

MSK MIND

MSK MIND is a new strategic research initiative to establish and accelerate integrative multimodal analysis of radiologic, histologic, genomic, molecular, laboratory and clinical data provisioned during the care and clinical research protocols of the MSK patient population.

MSK SPECTRUM

MSK SPECTRUM is a multi-modal, multidisciplinary prospective study of spatiotemporal determinants of High Grade Serous Ovarian Cancer (HGSOC) evolution, treatment and response.

The Multimodal Metabolism Map (MMM)

The Multimodal Metabolism Map (MMM) is a research initiative to collect, harmonize, and analyze high-dimensional metabolic data from primary tumor specimens and nearby normal tissues. This effort seizes on a combination of in-house and heterogeneously produced, publicly available metabolomic and transcriptomic measurements, and applies the resulting dataset to identify the critical metabolic alterations associated with the initiation and progression of malignancy, and the cell populations in the tumor microenvironment responsible for these alterations.

OncoKB

OncoKB is a precision oncology knowledge base and contains information about the effects and treatment implications of specific cancer gene alterations. It is developed and maintained by the Knowledge Systems group in the Marie Josée and Henry R. Kravis Center for Molecular Oncology at Memorial Sloan Kettering Cancer Center, in partnership with Quest Diagnostics and Watson for Genomics, IBM. Curated by a network of clinical fellows, research fellows, and faculty members at MSK, OncoKB contains detailed information about specific alterations in 632 cancer genes.

Software tools

Our labs invest heavily in developing robust software tools for both internal and external use with broad distribution through open source repositories. Visit one of our GitHub organization pages below for more information.

cBioPortal
Genome Nexus
OncoKB
Shahcompbio

Multi-Institutional Initiatives

Center for Integrated Cellular Analysis
Centers of Excellence in Genomic Science

The Centers of Excellence in Genomic Science (CEGS) program is run by the National Human Genome Research Institute, and supports formation of multi-investigator, interdisciplinary research teams to develop novel and innovative genomic technologies. Established in the summer of 2020, the Center represents a collaborative effort between six institutions in New York City.

IMAXT Grand Challenge:
Imaging and Molecular Annotation of Xenografts and Tumors (IMAXT)

To fully understand cancer, scientists need to know everything about a tumor – what types of cells are in it, how many there are and where they are located in the tumor. The Grand Challenge project aims to build a 3D tumor that can be studied using virtual reality and which shows every single different type of cell in the tumor.

IWG-PM

International Working Group for Prognostication in MDS is a prospective sequencing study of well-annotated clinical samples collected by clinical and research collaborators around the world. To support patient tailored clinical decision support, findings from this study will inform the WHO revision for MDS classification and will deliver the International Molecular Prognostic Scoring System for MDS. Additional information may be found here.